C-Aqm: A Crowd-Sourced Air Quality Monitoring System

Abstract

<p><strong>Abstract.</strong> European cities are currently facing one of the main evolutions of the last fifty years. “Cities for the citizens” is the new leitmotiv of modern societies, and citizens are demanding, among others, a greener environment including non-polluted air. Improved sensors and improved communication systems open the door to the design of new systems based on citizen science to better monitor the air quality. In this paper, we present a system that relies on the already available Copernicus Environment Service, on Air Quality Monitoring reference stations and on a cluster of new low-cost, low-energy sensor nodes that will improve the resolution of air quality maps. The data collected by this system will be stored in a time series database, and it will be available both to city council managers for decision making and to citizens for informative purposes. In this paper, we present the main challenges imposed by Air Quality Monitoring systems, our proposal to overcome those challenges, and the results of our preliminary tests.</p>

Mapping Air Quality With a Mobile Crowdsourced Air Quality Monitoring System (C-Aqm)

“…On the other hand, as it can be observed in Figure 5, the NO2 measurements are rather noisy, with a standard deviation of around 7 µg/m 3 , mainly due to a large quantification error of the NO2 sensor. As it can be observed in Figure 5, by applying a moving average filter of 1 hour and a correction of a constant bias on the measurements provided the NO2 sensor of the AirCrowd sensor node, the results achieved fulfill the precision and accuracy requirements (better than 25%) defined in (Parés, Vázquez-Gallego, 2018). 3.4 Air quality measurements system performance: Calibration procedure evaluation.…”

“…Then, an office operator can download the data from the database, correct the geo-referenciation, calibrate the system and finally generate the results. The functionalities of each subsystem are described in detail in (Parés, Vázquez-Gallego, 2018). Hereafter, a brief description is done.…”

“…In our previous work (Parés, Vázquez-Gallego, 2018), we developed a low-cost sensor node, named AirCrowd (Air Quality Crowd-sourced sensing device), which implements three basic functionalities:…”

“…Thus, we can imagine the trajectories followed by all the C-AQM users as a dense network with nodes that must share the same measurement values. We also assume that for short-term periods (less than 2 hours) the behaviour of sensor errors is quite stable and can be characterized mainly as a bias (Parés, Vázquez-Gallego, 2018). Consequently, a single least square adjustment of these network allows to calibrate all the sensors at once with an accuracy equivalent to the sensors noise.…”

“…In this paper, we present the validation process of the Crowdsourced Air Quality Monitoring (C-AQM) system (Parés, Vázquez-Gallego, 2018), which has been designed to generate high-resolution air quality maps using data from crowdsourced sensors and reference stations. As discussed in (Parés, Vázquez-Gallego, 2018) the development of the C-AQM system presents four main challenges: 1) to properly calibrate the low-cost sensors to ensure a performance good enough to use them as a complement of * Corresponding author reference stations and the Copernicus system; 2) the correct geo-referencing of all measurements, including those acquired inside urban canyons or tunnels; 3) the wireless transmission of measurements from thousands of sensor nodes to a Cloud server; and 4) the storage, analysis and representation of the information. In this paper, we shortly review the design and implementation of C-AQM and we mainly focus on the performance evaluation of the system regarding the calibration challenge.…”